MassIVE MSV000086016

Imported Reanalysis Dataset Public PXD000222

Comparative Phosphoproteomic Analysis of G2-checkpoint Recovery

Description

Comparative phosphoproteomic analysis of checkpoint recovery identifies new regulators of the DNA damage response. How cells recover from a DNA damage-induced arrest is currently poorly understood. We have performed large-scale quantitative phosphoproteomics to identify changes in protein phosphorylation that occur during recovery from a G2 arrest. We identified 154 proteins that were differentially phosphorylated in multiple experiments. Systematic depletion of each of these differentially phosphorylated proteins by siRNA identified at least 10 potential regulators of recovery. Data processing and bioinformatics: Raw data were converted to single DTA files using DTA SuperCharge and merged into Mascot Generic Format (MGF) files, which were searched using an in-house licensed Mascot v2.2 search engine against Human Swissprot 56.2 database concatenated with reversed sequences as decoy (containing 40656 sequences, 20328 forward sequences). Carbamidomethyl cysteine and oxidized methionines were set as fixed modifications; serine, threonine, and tyrosine phosphorylations were set as variable modifications; quantification was set with dimethyl double mode. The mass tolerance of the precursor ion was 10 ppm and 0.9 Da for fragment ions. The false discovery rate (FDR) was determined as < 1% (Mascot score threshold of 31) using the decoy database approach and the MGF files were trimmed at Mascot score threshold of 31 (1% FDR) by RockerBox. MSQuant v1.5 was used to quantitate the amounts of the identified phosphopeptides and determine the exact phosphorylation site within the peptide. Every phosphopeptide quantitation was manually validated; peptides with low signal:noise ratios, low number of MS scans, or overlapping peaks were not included for quantitative purposes. Histogram plots of the ratio of whole quantified peptides in each experiment were used to normalize the ratios. A program to extract information from MSQuant output was developed in-house to identify the position of each phosphorylation site and its status in current available databases (Phospho ELM and SwissProt). Panther Classification System was used to classify proteins with regulated phosphopeptides. NetworKIN was used to predict in vivo kinases for the phosphosites. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Phosphoproteomics ; DNA damage ; G2-checkpoint Recovery ; PLK1

Contact

Principal Investigators:
(in alphabetical order)
None Listed
Submitting User: ccms

Publications

Halim VA, Alvarez-Fernández M, Xu YJ, Aprelia M, van den Toorn HW, Heck AJ, Mohammed S, Medema RH.
Comparative phosphoproteomic analysis of checkpoint recovery identifies new regulators of the DNA damage response.
Sci Signal. 2013 Apr 23;6(272):rs9. Epub 2013 Apr 23.

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Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.